Results 161 to 170 of about 43,926 (306)

High productivity and multilayered circulation in the Late Cretaceous Arctic Ocean. [PDF]

Sci Adv
Liu S, Van Rooij D, Chen M, Fan H, Li G, Shi Y, Liu Y, Ng ZL, Luo K, Lin L, Zhuo H.   +10 more
europepmc   +1 more source

Anthromes and terrestrial carbon

PLANTS, PEOPLE, PLANET, EarlyView.
Anthony P. Walker, Rose Z. Abramoff, Kathryn Baragwanath, Matthew E. Craig, Yadvinder Malhi, Crystal N. H. McMichael   +5 more
wiley   +1 more source

Exploiting Aeolus winds in a regional numerical weather prediction model

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Aeolus measured winds have proven to be beneficial for global models. However, demonstrating positive impact for limited‐area models has been a challenge so far. For the first time, we have demonstrated a statistically significant positive impact of Aeolus winds in a limited‐area model by using the 4DVar data assimilation technique and the most recent ...
Gert‐Jan Marseille, Roohollah Azad, Martin Ridal, Susanna Hagelin   +3 more
wiley   +1 more source

Nanoplastic concentration and potential transport in the Arctic Ocean. [PDF]

NPJ Emerg Contam
Cai H, Carrier-Belleau C, Guilmette C, Massicotte P, Luthi-Maire A, Gigault J.   +5 more
europepmc   +1 more source

Hybrid physics–data‐driven modeling for sea ice thermodynamics and transfer learning

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Icepack–NN, a machine‐learning‐based hybrid version of the sea‐ice column model Icepack, is developed to correct state‐dependent forecast errors arising from misspecified snow thermodynamics, using neural networks applied online within the physical model.
G. De Cillis, A. Carrassi, J. Brajard, L. Bertino, M. Broccoli, D. Iovino, T.S. Finn, M. Bocquet   +7 more
wiley   +1 more source

Towards improving Arctic mixed‐phase cloud representation in the ECMWF model using MOSAiC observations

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Abstract The presence of Arctic clouds plays a crucial role in the evolution of the surface temperature of Arctic sea ice. However, large biases in cloud representation remain in state‐of‐the‐art weather and climate models. In this study, we use observational data from the one‐year Arctic ship campaign Multi‐disciplinary drifting Observatory for the ...
Luise Schulte, Richard Forbes, Linus Magnusson, Vera Schemann, Jonathan Day, Susanne Crewell   +5 more
wiley   +1 more source

The Arctic in world affairs : a North Pacific dialogue on Arctic futures : emerging issues and policy responses : 2016 North Pacific Arctic Conference proceedings

, 2016
The East-West Center and the Korea Maritime Institute have co-sponsored the 2016 North Pacific Arctic Conference (NPAC) held at the East-West Center, Hawaii Imin International Conference Center, Jefferson Hall, from Aug 9-12 2016.For more about the East ...
East-West Center, Kim, Yoon Hyung, Young, Oran R., Korea Maritime Institute, Corell, Robert W., Kim, Jong Deog   +5 more
core  

The benefits of a hybrid‐3DEnVar data assimilation scheme for the convection‐permitting NWP model AROME–Austria

Quarterly Journal of the Royal Meteorological Society, EarlyView.
The climatological‐error covariance matrix used in three‐dimensional variational data assimilation (3DVar) provides smooth and isotropic increments spread to long distances. In contrast, three‐dimensional ensemble variational data assimilation (3DEnVar) with a purely ensemble‐error covariance matrix provides inhomogeneous increments and contains the ...
Kaushambi Jyoti, Philipp Griewank, Florian Meier, Martin Weissmann   +3 more
wiley   +1 more source

Nuclear waste radionuclides unveil three decades of anthropogenic carbon in the Canada Basin of the Arctic Ocean. [PDF]

Nat Commun
Payne A, Raimondi L, Wefing AM, Vockenhuber C, Pérez-Tribouillier H, Williams W, Zimmermann S, Casacuberta N.   +7 more
europepmc   +1 more source

Impact of data assimilation on Arctic sea‐ice thickness variability and its coupling with atmospheric forcing

Quarterly Journal of the Royal Meteorological Society, EarlyView.
We document for the first time how the assimilation of CS2SMOS observations improves the model representation of Arctic sea‐ice thickness (SIT) and its variability: biases are reduced (top row), while excessive variability in the Beaufort Sea and lack of variability in the ice pack are both corrected (bottom row).
Jiping Xie, Yue Ying, Richard Davy, Laurent Bertino   +3 more
wiley   +1 more source